1. Technical Field
The present invention relates to iris recognition and more particularly to systems and methods which employ a reduce iris code for more efficient iris comparisons.
2. Description of the Related Art
A texture of the human iris has been shown to have excellent individual distinctiveness and thus is suitable for use in reliable identification. A conventional iris recognition system unwraps the iris image and generates a binary feature vector by quantizing the response of selected filters applied to the rows of this image.
The iris may be segmented and unwrapped into a rectangular image. From the unwrapped iris, texture is extracted by applying a Gabor filter bank. This is encoded into a binary image, known as the iris code that serves as the feature vector for recognition. Some regions of the iris provide more consistent texture than others. For example, pupil dilation causes the pupil-adjacent texture to be particularly volatile, and the presence of eyelashes or eyelids can substantially alter an iris code's appearance if they are not properly masked out. Moreover, the radial unwrapping technique is tuned to over-sample the area closest to the pupil while under-sampling the region where the iris meets the scelera. The band in the middle iris provides a more personal description. This region maps to the ciliary zone of the iris.
There has been some work attempting to isolate regions of the iris code which are either inconsistent (fragile) or, conversely, less stable. These studies looked directly at the final binary representation. Inconsistent bits were discovered by analyzing several binary iris codes of the same eye and counting the number of times a bit was a one or a zero. When bits that had a high variability were masked out, the false reject rate was reduced. This work discovered a fragile bit mask for each person in a gallery.
Other researchers have examined the effect of smaller iris codes on recognition and generate an iris code from the outer and inner rings of the iris. These techniques empirically show that texture closer to the pupil may perform better in recognition than texture closer to the sclera. Similarly, sampling rates were adjusted to generate smaller iris codes. These approaches reduce the size of iris code by adjusting the way the iris is unwrapped, but these works fail to assert that any portion of the iris should be favored when dealing in the context of iris recognition.
There has been some work attempting to isolate regions of the iris code which are either inconsistent (fragile) or, conversely, more discriminative. These studies looked directly at the final binary representation. Inconsistent bits were discovered by analyzing several binary iris codes of the same eye and counting the number of times a bit was a one or a zero. Sampling rates are adjusted to generate smaller iris codes. However, these approaches reduce the size of iris code by adjusting the way the iris is unwrapped. These techniques change the format of the code, which impairs the backward compatibility of the representation (e.g. with regards to rotation compensation).